Abstract
Online communities have become a tool for researchers to understand and help individuals with depression. According to their operation mode in terms of management, communities can be divided into management depression communities (MDCs) and lacking-management depression communities (LDCs). This study aimed to investigate the characteristics and impact of LDCs in comparison with MDCs. All postings from the previous year were collected from the LDC and MDC. Keywords were extracted and coded to identify the themes, and a text classifier was built to identify the type of emotions and social support expressed in the postings. Community members were then clustered to explore their different participation patterns. We found that in the LDC, the expression of negative emotions was the most popular theme, there was a lack of information about the treatment of depression and a lack of social support providers, the level of engagement of providers was low, and support seekers did not receive attention. These results reveal the need for community management and can be used to develop more effective measures to support members of online depression communities.